{"id":"https://openalex.org/W4415213097","doi":"https://doi.org/10.1016/j.cviu.2026.104781","title":"Synthetic frequency patterns injection for data-agnostic deepfake detection","display_name":"Synthetic frequency patterns injection for data-agnostic deepfake detection","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W4415213097","doi":"https://doi.org/10.1016/j.cviu.2026.104781"},"language":"en","primary_location":{"id":"doi:10.1016/j.cviu.2026.104781","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cviu.2026.104781","pdf_url":null,"source":{"id":"https://openalex.org/S185008460","display_name":"Computer Vision and Image Understanding","issn_l":"1077-3142","issn":["1077-3142","1090-235X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Vision and Image Understanding","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.cviu.2026.104781","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036992475","display_name":"Davide Alessandro Coccomini","orcid":"https://orcid.org/0000-0002-0755-6154"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Davide Alessandro Coccomini","raw_affiliation_strings":["ISTI-CNR, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0002-0755-6154","affiliations":[{"raw_affiliation_string":"ISTI-CNR, Pisa, Italy","institution_ids":["https://openalex.org/I122991210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038570344","display_name":"Roberto Caldelli","orcid":"https://orcid.org/0000-0003-3471-1196"},"institutions":[{"id":"https://openalex.org/I4210132817","display_name":"Mercatorum University","ror":"https://ror.org/03znjxt55","country_code":"IT","type":"education","lineage":["https://openalex.org/I4210132817"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Roberto Caldelli","raw_affiliation_strings":["CNIT, Florence, Italy","Universitas Mercatorum, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0003-3471-1196","affiliations":[{"raw_affiliation_string":"CNIT, Florence, Italy","institution_ids":[]},{"raw_affiliation_string":"Universitas Mercatorum, Rome, Italy","institution_ids":["https://openalex.org/I4210132817"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072879702","display_name":"Claudio Gennaro","orcid":"https://orcid.org/0000-0002-3715-149X"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Claudio Gennaro","raw_affiliation_strings":["ISTI-CNR, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ISTI-CNR, Pisa, Italy","institution_ids":["https://openalex.org/I122991210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046146028","display_name":"Giuseppe Fiameni","orcid":"https://orcid.org/0000-0001-8687-6609"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Giuseppe Fiameni","raw_affiliation_strings":["NVIDIA AI Technology Center, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA AI Technology Center, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072396889","display_name":"Giuseppe Amato","orcid":"https://orcid.org/0000-0003-0171-4315"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giuseppe Amato","raw_affiliation_strings":["ISTI-CNR, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0003-0171-4315","affiliations":[{"raw_affiliation_string":"ISTI-CNR, Pisa, Italy","institution_ids":["https://openalex.org/I122991210"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047189288","display_name":"Fabrizio Falchi","orcid":"https://orcid.org/0000-0001-6258-5313"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Fabrizio Falchi","raw_affiliation_strings":["ISTI-CNR, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0001-6258-5313","affiliations":[{"raw_affiliation_string":"ISTI-CNR, Pisa, Italy","institution_ids":["https://openalex.org/I122991210"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047189288"],"corresponding_institution_ids":["https://openalex.org/I122991210"],"apc_list":{"value":2370,"currency":"USD","value_usd":2370},"apc_paid":{"value":2370,"currency":"USD","value_usd":2370},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01270059,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"268","issue":null,"first_page":"104781","last_page":"104781"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9747999906539917,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9747999906539917,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9735999703407288,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9316999912261963,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.8744000196456909},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5195000171661377},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.48669999837875366},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4657000005245209},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4154999852180481}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.8744000196456909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7508999705314636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5566999912261963},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5195000171661377},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.48669999837875366},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4657000005245209},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4196999967098236},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3862000107765198},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3199000060558319},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2614000141620636}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.cviu.2026.104781","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cviu.2026.104781","pdf_url":null,"source":{"id":"https://openalex.org/S185008460","display_name":"Computer Vision and Image Understanding","issn_l":"1077-3142","issn":["1077-3142","1090-235X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Vision and Image Understanding","raw_type":"journal-article"},{"id":"doi:10.2139/ssrn.5606942","is_oa":true,"landing_page_url":"https://doi.org/10.2139/ssrn.5606942","pdf_url":null,"source":{"id":"https://openalex.org/S4210172589","display_name":"SSRN Electronic Journal","issn_l":"1556-5068","issn":["1556-5068"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1318003438","host_organization_name":"RELX Group (Netherlands)","host_organization_lineage":["https://openalex.org/I1318003438"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.1016/j.cviu.2026.104781","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cviu.2026.104781","pdf_url":null,"source":{"id":"https://openalex.org/S185008460","display_name":"Computer Vision and Image Understanding","issn_l":"1077-3142","issn":["1077-3142","1090-235X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Vision and Image Understanding","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F5497039910","display_name":"Ministero dell'Istruzione e del Merito","ror":"https://ror.org/01ehyh486"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W4385486282","https://openalex.org/W4387967853","https://openalex.org/W4399310664","https://openalex.org/W4405662451"],"related_works":[],"abstract_inverted_index":{"Deepfake":[0],"detectors":[1,84],"are":[2,113,157],"typically":[3],"trained":[4,134],"on":[5,115],"large":[6],"sets":[7],"of":[8,49,92,100,170],"pristine":[9,87],"and":[10,75,164,181],"generated":[11,33],"images,":[12],"resulting":[13],"in":[14,90,150],"limited":[15],"generalization":[16,47,148],"capacity;":[17],"they":[18,156,172],"excel":[19],"at":[20,43],"identifying":[21],"deepfakes":[22,168],"created":[23],"through":[24],"methods":[25],"encountered":[26],"during":[27],"training":[28],"but":[29],"struggle":[30],"with":[31,135,152],"those":[32],"by":[34],"unknown":[35],"techniques.This":[36],"paper":[37],"introduces":[38],"a":[39],"learning":[40],"approach":[41,123,137,180],"aimed":[42],"significantly":[44],"enhancing":[45],"the":[46,57,67,98,178,183],"capabilities":[48,149],"deepfake":[50,102,143],"detectors.":[51],"Our":[52],"method":[53],"takes":[54],"inspiration":[55],"from":[56],"unique":[58],"\"fingerprints\"":[59],"that":[60],"image":[61],"generation":[62,103,130,162],"processes":[63],"consistently":[64],"introduce":[65],"into":[66],"frequency":[68,78,95],"domain.":[69],"These":[70,110],"fingerprints":[71],"manifest":[72],"as":[73],"structured":[74],"distinctly":[76],"recognizable":[77],"patterns.":[79],"We":[80],"propose":[81],"to":[82,108,140,159,176],"train":[83],"using":[85,124],"only":[86],"images":[88],"injecting":[89],"part":[91],"them":[93],"crafted":[94],"patterns,":[96],"simulating":[97],"effects":[99],"various":[101],"techniques":[104],"without":[105],"being":[106],"specific":[107,161],"any.":[109],"synthetic":[111],"patterns":[112],"based":[114],"generic":[116],"shapes,":[117],"grids,":[118],"or":[119],"auras.We":[120],"evaluated":[121],"our":[122,136],"diverse":[125],"architectures":[126],"across":[127],"25":[128],"different":[129],"methods.":[131,154],"The":[132],"models":[133],"were":[138,173],"able":[139],"perform":[141],"state-of-the-art":[142],"detection,":[144],"demonstrating":[145],"also":[146],"superior":[147],"comparison":[151],"previous":[153],"Indeed,":[155],"untied":[158],"any":[160],"technique":[163],"can":[165],"effectively":[166],"identify":[167],"regardless":[169],"how":[171],"made.The":[174],"code":[175],"use":[177],"proposed":[179],"reproduce":[182],"presented":[184],"experiments":[185],"is":[186],"available":[187],"at:":[188],"https://github.com/davide-coccomini/Deepfake-Detection-without-Deepfakes-Generalization-via-Synthetic-Frequency-Patterns-Injection":[189]},"counts_by_year":[],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-16T00:00:00"}
